TACOS Project: Redefining How We Map and Model Catchments Response

A few minutes before midnight on May 31, we submitted TACOS — Transferability of soil water process understanding Across sCales for flOod and shallow landSlide prediction — to the PRIN 2026 call (Prot. 2026P2HL9S). Five Research Units, 36 months, €1.49 M total budget, €1.19 M requested from MUR.

The question

How much does knowing the soil actually help us predict floods in small ungauged catchments and rainfall-induced shallow landslides — and at which spatial scales does that knowledge pay off?

The question sounds simple but is curiously unresolved. Operational frameworks for ungauged basins lean on climate, topography, and geology; soil tends to be either smoothed away or absorbed into calibration. Yet soil is the first interface water meets in the critical zone — its depth, layering, pore structure, macropore connectivity, hydraulic properties, and antecedent moisture decide whether intense rainfall infiltrates or runs off, and whether a slope holds or fails.

The idea: a data degradation experiment

The methodological heart of TACOS is straightforward to state, and (we believe) unusually clean. Hold the model fixed and progressively coarsen the soil inputs — high-resolution DSM from full field profiles (Scenario A) → national-scale soil databases (Scenario B) → global coarse products like SoilGrids (Scenario C) — then test the predictions against independent flood events and landslide inventories. Pre-declared metrics with a priori tolerances identify the soil-information ceiling: the coarsest scenario for which predictions remain reliable.

The point is not to demonstrate that better soil information is better — that's almost trivially true — but to find where the curve flattens. Where it does, expensive high-resolution soil mapping is not justified by predictive gains. Where it doesn't, it is. This is a decision rule public authorities can actually use to prioritise soil-monitoring investments.

Four knowledge gaps, four work packages

The project addresses four interlocking gaps:

KG1 — Hydrology-oriented soil mapping (WP2, led by RU_UniNA, F. Terribile). Existing maps were built for agronomy; their relevance for hydrological response has rarely been evaluated systematically. We re-derive uncertainty-aware soil classifications explicitly oriented toward hydrological behaviour, combining Sentinel-1/Sentinel-2/PRISMA, machine learning (Random Forest, Gradient Boosting, spatiotemporal Transformers), and targeted field campaigns.

KG2 — The scaling problem and the breakdown of continuum assumptions (WP3, led by RU_CNR, M. Rossi). Richards' equation works — until it doesn't. We investigate, experimentally and theoretically, the conditions under which preferential flow, macropore activation, and non-equilibrium effects overtake equilibrium-based formulations. The framework links flow-regime classification to a-priori-evaluable thresholds (soil type, antecedent moisture, rainfall intensity) that determine which governing equation enters the Scale-2 model.

KG3 — The soil-information ceiling (WP4, led by RU_UniPD, M. Borga). The data degradation experiment itself, run inside both hydrological (GEOframe, GEOtop, WHETGEO) and landslide-triggering (GEOtop-LFS, TRIGRS, SlideforMAP, LANDPLANER) frameworks.

KG4 — Regionalisation lacking pedologically meaningful storage (WP5, led by RU_PoliTO, P. Claps). Index-flood regionalisation across ~100 small catchments (FOCA / FOCA2), runoff-coefficient analysis via SEASONEX and SIREN, leave-one-region-out cross-validation with and without soil-derived covariates. If soil information does not reduce quantile error, we say so.

The pilot sites

We work across three nested scales:

• Scale 1 (pore → pedon → hillslope): laboratory infiltration experiments, X-ray microtomography (SkyScan 1273, 3.5 μm/voxel), tracer transport tests, and seasonal/interannual in-situ parameter monitoring.
• Scale 2 (hillslope → small basin): three pilot catchments spanning a useful range — Ressi (0.02 km², Italian pre-Alps; the long-term ecohydrological catchment of the Padova group), Sangone at Trana (145 km², mixed forest–agricultural), Cordevole at La Vizza (7 km², high-elevation Dolomitic). The Collazzone pilot area (Umbria, 90 km²) anchors the landslide work; Langhe (NW Italy, 600 km²) provides the statistical-benchmarking testbed via the 1994 widespread event.
• Scale 3 (regional → territorial): ~100 small catchments nationwide.

The team

The consortium pulls together complementary competences:

• RU_UniTN — R. Rigon, G. Formetta. Coordination, process-based modelling (GEOframe/GEOtop), hydrological connectivity, kinetic theory of unsaturated flow.
• RU_PoliTO — P. Claps (substitute PI), S. Tamea, P. Mazzoglio. Regional hydrology, flood frequency analysis, the FOCA and I²-RED national databases, regionalisation methodology.
• RU_UniNA — F. Terribile, G. Langella, N. Mzid. Pedology, Digital Soil Mapping, EO covariates, LANDSUPPORT legacy.
• RU_UniPD — M. Borga. Mountain basin response, debris flows, hillslope-to-channel transfer indices, geo-hydrological modelling.
• RU_CNR (IRPI / ISAFOM) — M. Rossi, M. Bancheri, R. De Mascellis, S. L. Gariano. Physical infiltration experiments, X-ray CT, shallow-landslide thresholds, preferential flow.

The five RUs commit 38.6 person-months of permanent-staff effort plus 11 new temporary contracts (~228 PM total).

What's next

If funded, TACOS would start in 2027. Either way, the proposal is now part of how I think about soil hydrology: not as a parameter to calibrate, but as an empirically measurable structural control whose value for prediction is a question we can settle by experiment rather than assertion.

The intellectual threads reach back through several conversations on this blog — DARTHs and participatory digital twins; the kinetic theory of unsaturated flow that replaces Richards' equation with a pore-occupancy distribution; the percolation-based reading of field capacity and macropore connectivity; the GEOframe ecosystem. TACOS is where these strands meet operational prediction in ungauged basins, with shallow landslides as the natural companion problem — same soil–water dynamics, different observable.

Thanks to the four co-PIs and their teams for the intense final weeks, and to the RETURN PNRR and AdBPo communities for the questions that made this proposal, in a real sense, write itself.

Bimodal pore size distribution and hillslope stability

This post is to highlight the work of Fabio Ciervo, a Ph.D. student of Mariolina Papa that I co-advised with Vincente Medina. His thesis had the merit to put together two nice aspects of the recent research on soils. The first came from the work of Nunzio Romano [1] and co-workers, who show consistently that many soils present a bi-modal distribution in porosity, with effects in the form of the soil-water-retention curves (SWRC), and hydraulic conductivity, once Burdine or Mualem's [2] theory is applied. The other is the novel theory of hillslope stability coming out from the joint work of Lu, Likos, and Godt (e.g. [3]).

Who wants to enjoy his thesis can find it here: Fabio Ciervo, Modeling hydrologic response of structured soil, University of Salerno, 2015.
The code, developed in Java, that solves Richards 1D equation using these bimodal SWRC can instead be found on Github.
The Thesis produced a first paper which is under review in Vadose Zone Hydrology Journal.

Some References (others in the Dissertation)

[1] -Romano, N., Nasta, P., Severino, P., and Hopmans, J.W., Using bimodal lognormal function to descrivbe soil hydraulic properties, Soil. Sci. Soc. Am. J.,  75(2), 468-480, 2011

[2] - Roth, K., Soil Physics, Institute of Environmental Physics, Heidelberg University,
D-69120 Heidelberg, Germany, 2012

[2] - Lu, N., and Godt, J., Hillslope hydrology and stability, Cambridge University Press, 2013

Ning Lu lectures on hillslope processes and (especially) stability, at the Summer School on Landslides

In 2013 University of Calabria organised a very interesting School on Landslide triggering (many thanks to Lino Versace, Giovanna Capparelli and Giuseppe Formetta).  I actually gave a hand to organised it, and  I also gave a lecture on Richards equation.  Waiting for the official post of the lectures at the school site (after which, I will remove my videos), I cannot wait anymore to have on-line the lectures by Ning Lu. He gave four talks taken out of his beautiful book, Hillslope Hydrology and Stability, written with Jonathan Godt, new coordinator of the USGS landslide hazards program, and former co-advisor of my Ph.D. student Silvia Simoni (her thesis here).  A must-watch for any guy in the field !

First talk: A brief conceptual history of soil hydrology and soil mechanics (from Chapter 6 of his book)

Second talk: About Steady infiltration (Chapter 3 of his book)

Third talk, part I: Strength of hillslope materials (Chapter 7 of his book)

Third talk, part II: Hydro-mechanical properties of hillslopes (Chapter 8 of the book)

https://www.youtube.com/watch?v=xokmTXgmTf8

Fourth talk, part I: Failure surfaces  (Chapter 9 the book)

Fourth talk, part II: Field based stability analysis (Chapter 10 of his book)

Guidelines for the Mapping of the Triggering of Landslides and Debris Flow

My studies on shallow landslides were not purely theoretical but directed to make safer the mountain environment in which I live. Therefore, since the beginning of my activities there was an effort to convert theoretical results into practical tools, which, in turn, helped research. These guidelines written for the Danube Flood Risk Project come with this attitude. The work was also supported by the IRASMOS EU Project and, more recently, from the Trento Province. While reading the guidelines themselves is probably the simplest way to approach the mapping of landslide triggering according to my perspective, I also make public the presentation that I gave last and this year on the subject.

The first presentation is an introduction to the subject of hydrological hazards in mountains areas and the topic of guidelines:



The second contains and comments some applications of the guidelines on catchments in Trentino.



All the operation seen (except for the very recent CI-SLAM model) can be reproduced using the tools in the Spatial Toolbox of uDig or using GEOtop.

References

Beven, K J and Kirkby, M J. 1979, A physically based variable contributing area model of basin hydrology Hydrol. Sci. Bull., 24(1),43-69

Beven, K, Rainfall-runoff modelling: the primer, Wiley, 2001

Borga, M., G. Dalla Fontana, F. Cazorzi, Analysis of topographic and climatic control on rainfall-triggered shallow landsliding using a quasi-dynamic wetness index, Jour. Hydrol., 268, 56-71, 2002
D’Odorico, P. and R. Rigon, Hillslope and channels contribution to the hydrologic response, Water Resour Res, 39(5) , 1-9, 2003

Lanni, C.; McDonnell, J. J.; Rigon, R., On the relative role of upslope and downslope topography for describing water flow path and storage dynamics: a theoretical analysis, Hydrological Processes Volume: 25 Issue: 25 Pages: 3909-3923, DEC 15 2011, DOI: 10.1002/hyp.8263

Lanni C., J. McDonnell JJ, Hopp L., Rigon R., "Simulated effect of soil depth and bedrock topography on near-surface hydrologic response and slope stability" in EARTH SURFACE PROCESSES AND LANDFORMS, v. 2012, (In press). - URL: http://onlinelibrary.wiley.com/doi/10.1002/esp.3267/abstract . - DOI: 10.1002/esp.3267

Lanni C., Borga M., Rigon R., and Tarolli P., Modelling catchment-scale shallow landslide occurrence by means of a subsurface flow path connectivity index, Hydrol. Earth Syst. Sci. Discuss., 9, 4101-4134, www.hydrol-earth-syst-sci- discuss.net/9/4101/2012/ doi:10.5194/hessd-9-4101-2012, (in press at HESS)

Other papers and material about landslides can be found in this blog following the "Landslides" label.

My Past Research on Shallow Landslide and Mass Flow Triggering

The role of hydrology in triggering mass movements was initially confronted with an implementation of the theories of Montgomery and Dietrich [1994] (MD), and the case of instability caused by surface runoff [A21, A26, A27].  The study then continued with the analysis of transient phenomena, that is the instabilities caused by the propagation of pressure waves in the unsaturated medium  [A31, A32], according to the theory by Iverson [2000] (I), and integrating  the two, MD1994 and I2000, views even in the case of rainfall of varying intensity [A21, J23].
Then, the simplified approach  (important in as so much as it highlighted some qualitative aspects of infiltration in the hillslopes) was supplanted by the use of the GEOtop model for the continual simulation of hydrological variables [A38, J26], and transient effects, within a minimal set of simplifications.  The use of GEOtop has allowed for the separation of the hydrological part, effectively modeled by GEOtop, and the geotechnical part, contained in the GEOtop-FS model [J26].  Particularly, the latter of these was the subject of a probabilistic treatment that introduced uncertainties into the main geotechnical parameters  [J26].
The paper [J26], and the thesis of Silvia Simoni introduced a systematic approach to the identification of areas of instability that made full use of the potential of on-site geophysical measurement campaigns and the a priori characterization of geotechnical properties of the soil in the laboratory, without using back analyses for the calibration of parameters as is generally done by simplified models.  The IRASMOS Reports [rep06, rep07 and rep08] represent a summary of the literature available on this subject which has been eventually refined in [rep09].

The most recent work  has been focused on trying to understand the dynamics of subsurface flow  in  by means of virtual experiments [A43] with GEOtop, and in more conceptualized terms to explicit the role of the variability of depth of soil [J33, J35, thesis of Cristiano Lanni]  with the model denominated CI-SLAM.  The result is the introduction of the concept of "hydrological connectivity" of the hillslopes, which is realized when a perched water table forms that covers the whole basin.  The connectivity concept bridged the gap between hillslope hydrology and basin hydrology, and has also consequences important for hillslopes' stability [J37]. In fact these concepts allows a better statistical identification of landslide areas, than previous similar models.  [J35] also contains a preliminary attempt to use the theories of self-organizing criticality in the context of instability propagation, which, evidently, heralds the actual landslide itself.

Paper [J46] faces the issues related to the choice of a certain parameterisation of the soil retention curves and analyses their relation to hillslope stability. It uses a new theory that uses double porosity, and estimates the stability with the use of the new theories by Lu, Likos and Godt.

References

In English:

[ J23] - D’Odorico, P., Fagherazzi G., Rigon R. Potential for landsliding: Dependenceon hyetograph characteristics J. Geophys. Res., Vol. 110, No. F1, F01007 10.1029/2004JF000127 10 February 2005

[J26] Simoni, S., F. Zanotti, G. Bertoldi and R. Rigon, Modelling the probability ofoccurrence of shallow landslides and channelized debris flows using GEOtop-FS, Hydrol. Process. 22, 532–545, 2008, DOI: 10.1002/hyp.6886

[J33] - Lanni, C.; McDonnell, J. J.; Rigon, R., On the relative role of upslope anddownslope topography for describing water flow path and storage dynamics:a theoretical analysis, Hydrological Processes Volume: 25 Issue: 25 Pages: 3909-3923, DEC 15 2011, DOI: 10.1002/hyp.8263

[J35] - Lanni C., J. McDonnell JJ, Hopp L., Rigon R., "Simulated effect of soil depthand bedrock topography on near-surface hydrologic response and slope stability" in EARTH SURFACE PROCESSES AND LANDFORMS, v. 2012, (In press). - URL: http://onlinelibrary.wiley.com/doi/10.1002/esp.3267/abstract . - DOI: 10.1002/esp.3267

[J37] Lanni C., Borga M., Rigon R., and Tarolli P., Modelling catchment-scale shallowlandslide occurrence by means of a subsurface flow path connectivity index, Hydrol. Earth Syst. Sci. Discuss., 9, 4101-4134, (in press at HESS)

[A31] - E. Cordano, P., Bartolini, Rigon R. A flexible numerical approach to solving a generalized Richards’ equation problem and some applications, 2004

[rep06]- Rigon R., Rickenmann D., Catalogue of causes and triggering thresholds (Ed), IRASMOS EU Project Deliverable 1.1, 2007

[rep07] - Rigon R. (Ed), State-of-the-art models: their transferability and model application, IRASMOS EU ProjectDeliverable 1.2, 2007

[rep08] - R. Rigon, State of the art of prediction techniques, IRASMOS EU Project Deliverable 1.3, 2007

[rep09] - R.Rigon, Franceschi, S., Monacelli, G., and Formetta, G., The triggering of landslides and debris flows and their mapping, Danube Flood Risk EU Project, 2012

[J46] - Ciervo F. ,  Casini F. , Papa M.N. ,  Rigon R., Some remarks on bimodality effects of the hydraulic properties on shear strength of unsaturated soils, Vadose Zone Hydrology, published electronically, doi:10.2136/vzj2014.10.0152, 2015

In Italian:

[A21] - D’Odorico, P., Fagherazzi S., Rigon R. Frane superficiali e idrologia deiversanti: Un possibile metodo di indagine. Atti del XXVIII Convegno di Idraulica e Costruzioni Idrauliche, vol. V, pp.177-184, 2002

[A26] - Tiso, C., Bertoldi G. and R. Rigon. Il modello Geotop-SF per la determinazione dell’nnesco di fenomeni di franamento e di colata. Atti del Convegno Iterpraevent 2004, Riva del Garda, 24-28 Maggio 2004

[A27] - Rigon, R., A. Cozzini, S. Pisoni, G. Bertoldi e A. Armanini. A new simple method for the determination of the triggering of debris flows. Atti del Convegno Interpraevent 2004, Riva del Garda, 24-28 Maggio 2004

[A32] - Cordano, E., Panciera R., Rigon R., Bartolini P. Sulla soluzione diffusiva dell’equazione di Richards. Atti del XXIX Convegno di Idraulica e Costruzioni Idrauliche, Settembre 2004

[A43] Lanni C., Cordano E., Rigon R., Tarantino A., Analysis of the effect of normaland lateral subsurface water flow on the triggering of shallow landslides witha distributed hydrological model. in from geomorphology mapping to dynamic modelling, Strasbourg: CERG, 2009. Atti di: A Tribute to Prof. Dr. Theo van ASCH, Strasbourg, 6th-7th February 2009

Soil Depth Estimation

Estimation of soil depth is crucial for the assessment of hillslope hydrological processes (e.g.
Tromp van Meerveld and McDonnell, 2006) and landslide stability (e.g Lanni et al., 2011, 2012).  Is a topic that had a lot of attention in the community of geomorphologists but indeed it remain still an open. In a recent paper (e.g. Lanni et al., 2012, under the final stage of review in HESS) we wrote a very short review:

"The spatial distribution of soil depth is controlled by complex interactions of many factors (topography, parent material, climate, biological, chemical and physical processes) (e.g., Summerfield, 1997, Pelletier and Rasmussen, 2009, Nicotina et al., 2011). As a result, soil depth is highly variable spatially and its prediction at a point is difficult. Moreover, soil depth survey is time consuming and soil depth is difficult to measure even for small basins (Dietrich et al., 1995). Various methods have been explored to allow the estimation of soil depth over landscapes. A process-based approach was suggested by Dietrich et al. (1995) for predicting the spatial distribution of colluvial soil depth. Based on this approach, topographic curvature may be considered a surrogate for soil production. Heimsath et al. (1997, 1999) validated the relationship between curvature and soil production based on observations of cosmogenic concentrations from bedrock in their Tennessee Valley site in California. This approach was incorporated into a landscape evolution model by Saco et al. (2006) to evaluate the dependence of soil production on simulated soil moisture. Roering et al. (1999) supported the idea that soil production follows a non linear equation and, therefore, modified the dependence of soil depth relationships. However, the various modeling approaches for predicting soil depth over landscapes, described above, showed only partial success (Tesfa et al., 2009).

In contrast to the process-based approaches, a number of studies have applied statistical methods to identify relationships between soil depth and landscape topographic variables (e.g., slope, wetness index, plan curvature, distance from hilltop, or total contributing area) (e.g. Gessler et al., 1993, Tesfa et al., 2009, Catani et al., 2010). Some of these works reported good predictive capabilities for these statistical relationships. For instance, Tesfa et al. (2009) report that their statistical models were able to explain about 50% of the measured soil depth variability in an out-of-sample test. This is an important result, given the complex local variation of soil depth."

Our short review possibly miss some interesting reference as the one by D'Odorico (2000) on a possible bi-stable evolution equation, and our little work in Bertoldi et al. (2006) that generalize Heimsath's to include random variaility in depth. 

However, reduction of soil depth formation simply to a geometrical factor (as implied by using equations with homogenous parameters) is clearly not enough. Pedologists know it. But so far I found only a few able to enter in the strict path of learning our equations. 

Anyway,  looking for R based hydrological resources I found this explanatory map by Roudier and Beaudette:

Looking at it gives clearly the idea that soil depth does not depend (only) on geometry. Where slope and curvature remain constant, anyway soil depth varies.

It is easy to think that it depend on variability in the geologic substrate,  soil cover (grass, plants), and soil use (for instance grazing or the presence of animals). But there is any pedologist out there which could help us to built a consistent quantitative theory ?

As usual, the references could be a starting point for a more in-depth literature search.

References

Catani, F., Segoni, S., and Falorni, G.: An empirical geomorphology-based approach to the spatial prediction of soil thickness at catchment scale, Water Resour. Res., 46, W05508, doi:10.1029/2008WR007450, 2010. 

Dietrich, W. E., Reiss, R., Hsu, M.-L., and Montgomery, D. R.: A process-based model for colluvial soil depth and shallow landsliding using digital elevation data, Hydrol. Processes, 9, 383 – 400, doi:10.1002/hyp.3360090311, 1995.

D'Odorico, P. (2000), A possible bistable evolution of soil thickness, J. Geophys. Res., 105(B11), 25,927–25,935, doi:10.1029/2000JB900253.

Gessler, P. E., Moore, I. D., McKenzie, N. J., and Ryan, P. J.: Soil landscape modeling and spatial prediction of soil attributes, Int. J. Geogr. Inf. Syst., 9, 421– 432, doi:10.1080/02693799508902047, 1995.

Heimsath, A. M., Dietrich, W. E., Nishiizumi, K., Finkel, R. C.: The soil production function and landscape equilibrium, Nature, 388, 358– 361, doi:10.1038/41056, 1997.

Heimsath, A. M., Dietrich, W. E., Nishiizumi, K., Finkel, R. C.: Cosmogenic nuclides, topography, and the spatial variation of soil depth, Geomorphology, 27, 151– 172, doi:10.1016/S0169-555X(98)00095-6, 1999.

Lanni, C., McDonnell, J.J., and Rigon, R.: On the relative role of upslope and downslope topography for describing water flowpath and storage dynamics: a theoretical analysis, Hydrological Processes, 25(25), 2011.

Lanni, C., McDonnell, J., Hopp, L. and Rigon, R.: Simulated effect of soil depth and bedrock topography on near-surface hydrologic response and slope stability, Earth Surf. Process. Landforms, 2012, doi: 10.1002/esp.3267.

Lanni, C., Borga M., Tarolli P., Rigon R., Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution , HESSD, 2012

Nicotina, L., Tarboton, D. G., Tesfa, T. K., Rinaldo, A.: Hydrologic controls on equilibrium soil depths, Water Resour. Res., 47, W04517, doi:10.1029/2010WR009538, 2011.

Liu, J., Chen, X., Lin, H., Liu, H., & Song, H. (2013). A simple geomorphic-based analytical model for predicting the spatial distribution of soil thickness in headwater hillslopes and catchments. Water Resources Research, n/a–n/a. doi:10.1002/2013WR013834

Pelletier, J. D. and Rasmussen, C.: Geomorphically based predictive mapping of soil thickness in upland watersheds, Water Resour. Res., 45, W09417, doi:10.1029/2008WR007319, 2009.

Roering, J.E., Kirchner, J.W., and Dietrich, W.E.: Evidence for nonlinear, diffusive sediment transport on hillslopes and implications for landscape morphology, Water Resorces Research, vol. 35(3), 853–870, 1999.

Saco, P. M., Willgoose, G. R., and Hancock, G. R.: Spatial organization of soil depths using a landform evolution model, J. Geophys. Res., 111, F02016, doi:10.1029/2005JF000351, 2006.

Summerfield, M. A.: Global Geomorphology, 537 pp. Longman, New York, 1997

Tesfa, T. K., Tarboton, D. G., Chandler. D. G., and McNamara, J. P.: Modeling soil depth from topographic and land cover attributes, Water Resour. Res., 45, W10438, doi:10.1029/2008WR007474, 2009.

Tromp-van Meerveld, H.J., and McDonnell, J.J.: Threshold relations in subsurface stormflow: 2. The fill and spill hypothesis, Water Resources Research, 42, W02411. 2006.